International Journal of Testing vol:9 issue:2 pages:151-166
This study introduces an approach for modeling multidimensional response data with construct-relevant group and domain factors. The item level parameter estimation process is extended to incorporate the refined effects of test dimension and group factors.
Differences in item performances over groups are evaluated distinguishing two levels of differential item functioning (DIF): a domain level and an item level. An illustration is presented using a Dutch spelling proficiency scale administered to two subgroups. DIF is modeled by the interaction between group and item domain (domain
level DIF), and by the interaction between groups and items within each domain (Item level DIF). A set of IRT Models was estimated using an adaptation of the logistic regression
approach. The model with domain specific item-by-group interactions or DIF performed better than the other models neglecting domain or group differences. The method appears to be promising in that explicit domain factors can be
implemented into model estimation procedure to better understand why items favor a specific language group over another.